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Title1
2
SharedMycobacterium avium genotypes observed among unlinked clinical and3environmental isolates4
5
Running Title6
7
Geographically dispersed genotypes of M. avium8
9
Authors10
11
M. Ashworth Dirac,# Kris M. Weigel, Mitchell A.Yakrus, Annie L. Becker, Hui-Ling12
Chen, Gina Fridley, Arthur Sikora, Cate Speake, Elizabeth D. Hilborn, Stacy Pfaller,13
Gerard A.Cangelosi#14
15
Work performed at:1617
Seattle Biomedical Research Institute, 307 Westlake Ave N, Seattle, Washington, U.S.A18
Centers for Disease Control and Prevention, Atlanta, Georgia, U.S.A.19
20
Affiliations21
22
University of Washington, Seattle (M.A.Dirac, K.M. Weigel, A.L. Becker, H.Chen,23
A.Sikora, C.Speake, G.A. Cangelosi); Seattle Biomedical Research Institute, Seattle24
(M.A. Dirac, K.M. Weigel, A.L. Becker, H.Chen, G.Fridley, A. Sikora, C.Speake, G.A.25
Cangelosi); Centers for Disease Control and Prevention, Atlanta (M. A.Yakrus); US26
Environmental Protection Agency, Research Triangle Park, North Carolina, U.S.A. (E.D.27
Hilborn), US Environmental Protection Agency, Cincinnati, OH, U.S.A. (S.Pfaller)28
29
The views expressed in this report are those of the individual authors and do not30
necessarily reflect the views and policies of the U.S. Environmental Protection Agency or31
the Centers for Disease Control and Prevention. Mention of trade names or commercial32
products does not constitute endorsement or recommendation for use.33
34
Present address:35
36
University of Washington Department of Environmental and Occupational Health37
Sciences, Box 357234, Seattle, Washington, U.S.A. (M.A. Dirac, K.M. Weigel, A.L.38
Becker, G.A. Cangelosi)39
40
41
42
#Corresponding authors: M. Ashworth Dirac ([email protected]) and Gerard A.43
Cangelosi ([email protected])44
Copyright 2013, American Society for Microbiology. All Rights Reserved.Appl. Environ. Microbiol. doi:10.1128/AEM.01443-13AEM Accepts, published online ahead of print on 12 July 2013
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Introduction64
Members of theMycobacterium avium complex (MAC) live in natural soils and65
water sources, commercial soils and treated water, and other man-made niches (1, 2). At66
least some strains cause diseases in susceptible humans, including lymphadenitis in67
children, disseminated disease in severely immunocompromised individuals, and lung68
disease associated with several clinical profiles (3). MAC comprises two major species,69
M. avium (MA) andM. intracellulare (MI), as well as minor species and members that70
are not classified into species (4-8). MA is further divided into subspecies,M. avium71
avium (MAA), M. avium silvaticum (MAS), M. avium paratuberculosis (MAP), andM.72
avium hominissuis (MAH) (9). Even within a single group, genomes can vary markedly73
among strains (10).74
High-resolution genotypic fingerprints are taken to be uniquely associated with75
specific strains of MAC. Several methods have been used to generate high-resolution76
genetic fingerprints of the MAC. These include pulsed-field gel electrophoresis (PFGE)77
(11), restriction-fragment-length polymorphism (RFLP) analysis using insertion78
sequences (12, 13), repetitive-sequence-based PCR (rep-PCR) analysis (14, 15),79
randomly amplified polymorphic DNA (RAPD) analysis (6), mycobacterial interspersed80
repetitive unit variable number tandem repeats (MIRU-VNTR) analysis (16), amplified81
fragment length polymorphism (ALFP) (17), and (CCG)4-based PCR analysis (18) and82
multispacer sequence typing (MST) (19). These methods vary in the quantity and purity83
of DNA required for analysis and their portability (the ease with which results can be84
compared across analyses and exchanged among laboratories). The hypothetical gold85
standard for validating genotypic fingerprinting methods would be complete genome86
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sequencing. In practice, however, methods are compared on the basis of their87
discriminatory index (DI), a quantity that reflects a methods probability of placing any88
two isolates into separate genotypic groups (20). Some validation is provided by the fact89
that multiple isolates from the same patient, either from separate anatomic sites or taken90
over time, often have the same fingerprint (11, 12, 17, 21, 22). When matching or highly91
similar fingerprints are found between patients (17, 21-23), in the same environmental92
source over time (22, 24), or between a patient and his environment (22, 23, 25-28),this93
is often interpreted as support for a link of some sort. These kinds of matches are94
interpreted to indicate a shared source of acquisition, continuous colonization, or a95
probable source of acquisition, respectively.96
Despite the utility of this approach (29), it is noteworthy that several studies using97
high-resolution genotyping methods have found matches or clusters between cases with98
no apparent shared sources (12, 15, 21, 30). Previous work in our laboratory used large-99
sequence polymorphism analysis (LSP analysis, aka deligotyping) and rep-PCR to show100
that the MA genome sequence strain, 104, was found in clinical isolate collections from101
Southern California and Northwestern Washington (15). An earlier study used rep-PCR102
and IS1245 RFLP to identify a group of clinical isolates from these same two locations103
that shared another genotype (14). More recently, a MIRU-VNTR analysis of 47 human104
isolates of MAfound high phylogenetic proximity between isolates collected over 2105
decades from a clinical site in Italy (31). These observations suggest that some MA106
genotypes are stable or have wide geographical distributions.107
In order to more rigorously assess the wide geographical distribution of some108
MAC strains, this study used high-throughput genotyping methods to characterize (179)109
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geographically diverse clinical and environmental isolates of MA. Many widely used MA110
genotyping methods, including IS1245 RFLP and PFGE, have limited portability and111
require large quantities of DNA. Thus, we chose to evaluate PCR-based typing methods112
with greater portability and smaller DNA requirements: 3 hsp65 sequencing, rep-PCR,113
MIRU-VNTR and deligotyping, to find one with sufficient reproducibility and114
discriminatory power for use in the larger analysis. Two methods were then applied to115
larger sets of isolates for our geographic analysis. Subsets were further analyzed by116
PFGE and MIRU-VNTR.117
Methods118
MA isolates. Genotypic analyses were carried out using subsets of a large MA119
isolate and DNA collection assembled at Seattle Biomedical Research Institute (Seattle120
BioMed) and currently housed at the University of Washington (UW). Permanent121
cultures or genomic DNA of archived MA isolates were received from multiple122
collaborators. The isolates and DNA samples used in this study were all previously123
described (14, 15, 22-26, 28, 32-39), and are listed in Supplementary Tables S1-S3. Most124
isolates were identified to the species level. In total, 127 clinical MA isolates (each from125
a separate individual case) and 52 environmental MA isolates were examined.126
Bacterial culture and preparation of genomic DNA. For some isolates, genomic127
DNA was received from collaborators. Isolates for which permanent cultures were128
archived at Seattle BioMed were grown on Middlebrook 7H10 containing 10% OADC129
(Fisher Scientific International, Hampton, NJ) at 37 C and, then, DNA was extracted by130
one of three methods: by boiling, using the ArchivePure DNA Cell/Tissue Kit (5 Prime,131
Gaithersburg, MD), or using the UltraClean Microbial DNA Isolation Kit (MoBio132
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Laboratories, Carlsbad, CA). The ArchivePure protocol was modified for mycobacteria133
as shown in Supplementary Information S4. The MoBio kit was employed using the134
recommendations for mycobacterial species from Bacterial Barcodes, and for some135
isolates the MoBio method was modified by adding a freeze-thaw step after suspending136
cells in Bead Solution but before vortexing, or as described previously (40). Extracted137
DNA ranged in concentration from 10-250 ng/uL and was not adjusted in the following138
analyses unless otherwise noted.139
PCR and sequencing ofhsp65. A 1,059 bp portion of the variable 3 end of the140
hsp65 gene was PCR-amplified and sequenced. Amplification primers were141
MAChsp65F_574 (5-CGGTTCGACAAGGGTTACAT-3) and MAChsp65R (5-142
ACTGACTCAGAAGTCCATG-3) as reported in Turenne et al(41). PCR mixtures143
consisted of 5 g of genomic DNA, 1X PCR buffer with MgCl2, 0.2 mM of dNTPs, 1 U144
of EconoTaq, (Lucigen, Middleton, WI), 1 M betaine, (Sigma, St Louis, MO) 5 M of145
forward and reverse primer, and Type 1 purified water (Barnstead Nanopure) to adjust146
the final volume to 25 L. Cycling conditions were 95 C for 10 minutes, followed by 35147
cycles of 95 C for 1 minute, 55 C for 1 minute, and 72 C for 90 seconds, and then a148
final 10 minutes at 72 C. Products were visualized by electrophoreses, purified with149
Qiaquick Spin PCR purification kit (QIAGEN, Valencia, CA) and submitted for150
sequencing using an Applied Biosystems 3730XL Genetic Analyzer. PCR primers and an151
additional primer (hsp65-1047R: 5-GTAGTCGGAGTCGGTGTTCT-3) were used for152
sequencing. Hsp65 codes were assigned according to the nomenclature of Turenne et al153
(41) and novel sequences were reported to GenBank.154
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MIRU-VNTR analysis. MIRU-VNTR analysis was carried out using primer155
sequences from Thibault et al(16).For loci 3, 7, 10, 25, 32, 47 and 292, PCR mixtures156
consisted of: 2.5 L genomic DNA extraction, 1X PCR buffer with MgCl2, 0.2 mM157
dNTPs, 1 U EconoTaq, 1 M betaine, 2.0 M of each primer, and nanopure water to adjust158
the final volume to 25 L. Reactions for loci 3 and 32 also contained 1.0 L of dimethyl159
sulfoxide. For locus X3, the volume of genomic DNA extraction used was reduced to 1160
L. Cycling conditions for loci 3, 7, 10, 25, 32, 47 and 292 were: 10 min at 95 C,161
followed by 40 cycles of 95 C for one min, 58 C for one min and 72 C for 30 sec, and162
then a final 10 min at 72 C. Cycling conditions for reactions at locus X3 consisted of 5163
min at 94 C, followed by 40 cycles of 94 C for 30 sec, 58 C for 30 sec, and 72 C for164
30 sec, then a final 10 min at 72 C. Products were analyzed on 1.0-2.0% agarose gels165
stained with ethidium bromide.166
Because four of the eight MIRU loci described by Thibault et al(16) showed167
notably greater allelic diversity than the other four, we considered both eight-locus and168
four-locus MIRU (alone or in combination with other methods), as possible169
fingerprinting methods for this study. In particular, we evaluated the replacement of the170
four least-variable MIRU loci with four LSP loci that appeared to be more variable,171
thereby achieving greater resolution in a total of 8 PCR reactions. MIRU types were172
assigned to represent the number of repeats inferred to be present from the product length173
at that locus, based on product sizes and repeat numbers from Thibault et al(16) and174
personal correspondence with V. Thibault and F. Biet.175
LSP analysis. LSP analysis was carried out at four genomic loci: HSDR, LSP2176
(aka DA2), LSP7 (aka DA7), and LSPP5 (aka DEL11), using published primer sequences177
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(15). For most isolates, LSP analysis was carried out on 1 L of genomic DNA using the178
GC-Rich PCR System (Roche Diagnostics, Basel, Switzerland), as described (15). For a179
small number of isolates, EconoTaq was used with the following reaction mixture: 1 L180
genomic DNA, 1X PCR buffer with MgCl2, 0.2 mM dNTPs, 1 U EconoTaq, 1 M betaine,181
0.6 M of each primer, and nanopure water to adjust the final volume to 25 L.182
Visualization and nomenclature employed have been previously described(15).183
LSP-MVR analysis. An eight-digit genotype combining information from LSP184
and MIRU-VNTR analyses was assigned. The first four digits represent results for the185
four LSP loci, and the last four digits represent results for the MIRU-VNTR loci that186
showed the highest allelic diversity in Thibault et al: X3, 25, 32 and 47. We refer to this187
combined approach as LSP-MVR analysis.188
Rep-PCR. Rep-PCR was carried out using the Bacterial Barcodes mycobacterial189
kit (Athens, GA) as described (14, 15). Results for isolates analyzed in separate PCRs190
and on separate chips were combined into a single report using the Diversilab software,191
and letter type designations were assigned to branches of the dendrogram with at least192
92% average similarity.193
PFGE. PFGE of MA isolates was carried out using previously described methods194
(11). Patterns considered indistinguishable by the Tenover criteria (29) were assigned195
numeric type designations.196
Calculation of DI. Assessment of DI was conducted on a 20% random sample of197
all clinical MA isolates for which DNA was stored at Seattle BioMed at the outset of the198
study. A uniform distribution in Microsoft Excel was used to assign a random number199
between 0 and 1 to each sample. Samples with random numbers of 0.20 or less (N = 29)200
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were subjected to multiple genotyping methods. One of the selected genomic DNA201
samples was exhausted before all methods could be applied, so 28 samples were used to202
evaluate discrimination. The DI of each method was calculated using the approach of203
Hunter and Gaston (20) as implemented by BioPHP at204
http://biophp.org/stats/discriminatory_power/demo.php205
Identification of GDCs. Genomic DNA from a convenience sample of 127206
clinical MA isolates was subjected to LSP-MVR analysis. Each clinical isolate was207
classified as having a unique genotype, sharing its genotype only with other clinical208
isolates from the same location, or sharing its genotype with at least one clinical isolate209
from another location. These latter genotypes were termed geographically dispersed210
clinical types, or GDC types.211
Environmental comparison. Genomic DNA from a convenience sample of 52212
environmental MA isolates was subjected to LSP-MVR analysis.213
Ethical review. This study was determined by the investigators to be exempt214
under 45 CFR 46.101.b.4.215
Results216
Selection of PCR-based genotyping methods. In order to assess reproducibility217
within each method,DNA extracted from isolates HMC02 and 104 was subjected to218
hsp65 sequencing five times, rep-PCR 11 and 8 times, and LSP-MVR more than seven219
times. Identical hsp65 sequencing results were seen all five times. Eighty-five percent of220
all possible pair-wise comparisons between rep-PCR runs of HMC02 (47 of 55) were221
92% similar, and 88% (7 of 8) of replicate rep-PCR runs of 104 were 92% similar.222
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LSP-MVR results were identical for HMC02 on every occasion and identical for 104 all223
but one time.224
To compare DIs, all PCR-based methods were applied to the panel of 28225
randomly selected clinical isolates (Supplementary Table S1). Hsp65 sequencing alone226
had a DI of 0.58, LSP of 0.87, four-locus MIRU of 0.84, and eight-locus MIRU of 0.87,227
rep-PCR of 0.97 (Table 1). The combination of four LSP and four MIRU-VNTR loci228
(LSP-MVR) improved the DI to 0.95. When combined with LSP, the use of eight MIRU-229
VNTR loci did not improve resolving power over the use of four MIRU-VNTR loci230
(Table 1). Thus, LSP-MVR, with four LSP and four MIRU-VNTR loci, exhibited high231
resolving power in a high-throughput, portable, PCR-based method, and was chosen as232
the first-line approach for the further analysis.233
Identification of geographically dispersed clinical strains. Clinical MA isolates234
from 127 individuals were typed by LSP-MVR. Of these, 24 (19%, 24/127) had235
genotypes unique among clinical isolates. The remaining 103 isolates had one of 18 non-236
unique genotypes. Of these 18 non-unique genotypes, six genotypes were found only in237
one geographic collection. Twelve genotypes were found at more than one geographic238
location. Isolates exhibiting these geographically dispersed clinical (GDC) genotypes239
accounted for 50% (63/127) of all typed clinical isolates.240
GDCs by location are shown in Figure 1; other LSP-MVR genotypes observed241
among clinical isolates are shown in Supplementary Table S5. GDC1 includes isolate242
HMC02 and some genotypically similar isolates previously identified by rep-PCR and243
IS1245 RFLP (14, 15). GDC6 and GDC7 both contain some isolates previously244
characterized by rep-PCR as 104-like (14, 15). Strain 104, itself, shared its LSP-MVR245
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type only with other clinical isolates from its region of isolation, Southern California. The246
other GDCs have not previously been described.247
Although 8-locus MIRU-VNTR had a lower DI than LSP-MVR (Table 1), it is a248
widely used method that increased in popularity over the course of this study. Therefore,249
apost hoc analysis was conducted to determine if GDCs identified by LSP-MVR would250
likely have been identified if the main analysis had been carried out by using 8-locus251
MIRU-VNTR, instead. Complete 8-locus MIRU-VNTR types were determined for the252
isolates randomly selected to evaluate the DIs of genotyping methods (Supplementary253
Table S1) and for the isolates selected for PFGE analysis (Table 2). Thus, 8-locus254
MIRU-VNTR results were available for at least two isolates from different geographical255
locations within 4 GDCs defined by LSP-MVR (GDC1, GDC2, GDC3 and GDC7).256
Three of the 4 GDCs contained multiple isolates from different locations with the same 8-257
locus MIRU-VNTR genotype (Supplementary Table S6). Therefore, these GDCs would258
have been identified if this widely-used approach had been employed in the main259
analysis.260
A subset of clinical isolates was further analyzed by PFGE (Figure 2). These261
isolates were chosen for their membership in GDCs defined by LSP-MVR and the262
availability of permanent cultures (required for PFGE). For two GDCs (GDC1 and263
GDC7), at least one isolate from more than one geographic location was available for264
PFGE analysis (Table 2). In both of these GDCs, two isolates from distant sites exhibited265
indistinguishable PFGE patterns.266
GDC genotypes among environmental isolates. The occurrence of GDC267
genotypes in the environment was investigated. MA isolates from 52 water, food and soil268
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samples were typed by LSP-MVR. Thirty-three isolates (63%, 33/52) from two distinct269
Western U.S. geographic locations shared a single genotype, GDC1. Five additional270
GDCs were observed (GDC5, 9, 10, 11, 12) in environmental collections, accounting for271
13 additional isolates (25%, 13/52). Only six environmental isolates (12%, 6/52) had272
genotypes not observed in the clinical collections. Genotypes observed among273
environmental isolates by location are shown in Supplementary Table S7.274
Discussion275
Studies on the epidemiology and etiology of MAC diseases have often compared276
the genetic fingerprints of MAC isolated from patients clinical specimens and the277
environments to which those patients have been exposed (22, 23, 25-28). Few of these278
studies were conducted in a comparative fashion, and the underlying distribution of MAC279
in the environment is only partially understood. To date, we know of only one study, that280
of Fujita et al (42), that included MAC isolated from the environments of non-diseased281
individuals.282
Studies of the epidemiology ofM. tuberculosis have been aided by the use of283
PCR-based strain typing methods, namely MIRU-VNTR and spoligotyping. The284
portability of these methods is such that results generated by independent investigators285
around the world can be fed into unified numerical databases (43, 44). At the outset of286
the present study, no such portable methods had emerged for MAC. Therefore, we287
combined two previously reported, moderate-resolution methods, LSP analysis and288
MIRU-VNTR (15, 16), to yield a simple, highly reproducible approach with resolving289
power that approaches those of well-characterized methods such as PFGE and IS1245-290
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RFLP. LSP-MVR is inexpensive to perform, requires only small amounts of DNA, and291
yields portable results.292
LSP-MVR analysis identified distinct genotypic groups among MA isolates from293
clinical cases separated by distance and without identified epidemiologic links. Forty-two294
genotypes were observed among 127 clinical isolates. Twelve genotypes (GDC1 -295
GDC12) were observed at multiple geographic locations, isolated from patients with no296
apparent connection with each other. This may reflect common exposure to commercial297
products such as food or potting soil, which are shipped across long distances and are298
known to be colonized by MAC (1, 26). It may also reflect the presence of these299
genotypes in environmental sources at multiple, distant locations. These genotypes may300
have traits that favor exposure to humans, such as survival in shipped products, built301
environments, domestic water supplies, or domesticated animals. They may have302
characteristics that favor colonization, invasion, or pathogenicity in human hosts.303
Alternatively, these results could be an artifact of the genotyping approach. These304
results were obtained using a novel method, but it is likely that other established305
genotyping methods would yield similar results for several reasons. First, LSP-MVR306
showed good resolving power. It displayed a DI of 0.95 in a random set of clinical MA307
isolates. This value approached a DI of 0.97 observed for rep-PCR using the same308
isolates, and exceeded that of the widely-used 8-locus MIRU-VNTR (0.87).309
Secondly, the existence of GDCs has been partially corroborated by use of other310
methods: IS1245-RFLP, PFGE, rep-PCR and MIRU-VNTR. Three GDCs identified in311
the present study, GDC1, GDC6, and GDC7, include isolates previously reported to share312
IS1245-RFLP patterns (14, 15). In the present study, GDC1 and GDC7 contained313
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geographically distant members that shared PFGE patterns. Likewise, for the four GDCs314
identified by LSP-MVR in this study that had sufficient 8-locus MIRU-VNTR data to315
evaluate (GDC1-3 and GDC7), 3 of 4 GDCs were confirmed. Thus, the combined high-316
resolution genotypic data support the conclusion that some genotypes are geographically317
widespread.318
Our observations are consistent with a recent MIRU-VNTR study of 47 clinical319
isolates collected over 2 decades from a single clinical site in Italy (31). Although the320
Italian isolates were not separated geographically, the authors concluded that some MA321
genotypes are stable over time and can be associated with epidemiologically unlinked322
cases. Our study, which applied a higher-resolution method (LSP-MVR) to a larger and323
more diverse sample set (179 clinical and environmental isolates from geographically324
distinct sources), confirms and extends these conclusions.325
Six GDC genotypes (GDC1, 5, 9, 10, 11 and 12) were observed in isolates from326
environmental samples. Therefore, GDC genotypes are not unique to clinical isolates.327
Genotypic diversity appeared to be lower among the environmental isolates examined328
than among the clinical isolates examined. Limited genotypic diversity among329
environmental isolates has been reported elsewhere (23, 24), and must be interpreted with330
caution. It may be due to selection by methods of sample collection, decontamination331
and culture, or peculiarities of the environments represented in the convenience sample332
typed. It may also imply that high-resolution genotyping methods that were developed333
for use with clinical MAC isolates may not have the same ability to distinguish334
environmental isolates. In other words, the molecular markers that vary among clinical335
MAC strains may be less variable among environmental strains, despite a high level of336
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diversity at other loci. Alternatively, it may reflect truly low genotypic diversity among337
MA in any given environment. The greater diversity seen among clinical isolates may338
reflect the fact that humans are exposed to many different environments, and thus are339
able to reflect the diversity across different environments more effectively than340
purposeful environmental sampling.341
Our results suggest that caution should be employed in interpreting genotypic342
matches between clinical and environmental isolates in studies of MAC lung disease that343
do not include appropriate control-subjects. Matches between rarely observed genotypes344
of MA may provide evidence for an acquisition event, but the observation of common345
genotypes at distant sites shows that some genotypic matches can occur in the apparent346
absence of an epidemiologic link. When Tenoveret alpresented their criteria for347
interpreting PFGE data in epidemiologic investigations, they emphasized that high-348
resolution genotypic data should be applied in the context of an outbreak investigation349
with a defined time frame, knowledge of the endemic strains of a pathogen in the region,350
and other epidemiologic data (29). The importance of this context was recently noted by351
investigators of a nationwide Salmonella outbreak associated with fresh produce (45).352
This context is infrequently present in studies of human disease caused by MAC.353
The timing of etiologically relevant exposures is unknown and the underlying distribution354
of strains in the environment is poorly characterized. In genotypic studies to date, other355
epidemiologic data are often limited and comparator groups are rarely included.356
Comparison to representative control-subjects, or development of an expanded357
worldwide genotypic database will facilitate the interpretation of molecular358
epidemiological data in studies of MAC disease. Use of PCR-based genotyping359
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technologies with portable, numerical results, such as LSP-MVR, will further assist in360
large-scale, multi-site studies and development of shared databases.361
362
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Acknowledgements363
This publication was developed under a STAR Research Assistance Agreement364
(No. FP 91695601) and a Collaborative Agreement (No. 833030010) awarded by the365
U.S. Environmental Protection Agency. Additional funding was provided to M.A. Dirac366
by the Medical Scientist Training Program (T32 GM07266, a National Research Service367
Award (NRSA) from the NIGMS (National Institute of General Medical Sciences)).368
We thank Joseph Falkinham, Marcel Behr, Sylvia Leao, Richard van Soolingen369
and Carolyn Wallis for strains and DNA samples provided.370
371
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Table 1. Discriminatory indices of genotyping methods forMycobacterium avium.569
Method Discriminatory index
Alone + hsp65 + LSP + 4-locus MIRU + 8-locus MIRU + rep-PCR
hsp65* 0.58 ------------ 0.91 0.89 0.91 0.98
LSP* 0.87 ------------ ------------ 0.95 0.95 0.97
4-locus MIRU* 0.84 ------------ ------------ ------------ ------------ 0.98
8-locus MIRU* 0.87 ------------ ------------- ------------ ------------ 0.98
rep-PCR* 0.97 ------------ ------------ - ----------- ------------ ----------------
*hsp65 = sequencing of a 1,059bp portion of the 3 end of the gene for heat shock protein 65; LSP = large-sequence570
polymorphism analysis; 4-locus MIRU = MIRU/VNTR or mycobacterial interspersed repetitive unit/variable-number571
tandem repeats analysis using loci X3, 25, 32 and 47; 8-locus MIRU = MIRU/VNTR or mycobacterial interspersed572
repetitive unit/variable-number tandem repeats analysis using loci 292, X3, 25, 47, 3, 7, 10 and 32; rep-PCR = repetitive-573
sequence-based PCR574
575
576
577
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578
Table 2. Pulsed-field gel electrophoresis of some clinical isolates sharing GDC* genotypes.579
Name LSP-MVR type
Isolate ID Site PFGE pattern
GDC1 2112-3383 4904 Montreal 10
HMC02 Seattle Not interpretable
108 Southern California 11
W355 Southern California 10
03240 Montreal 13
GDC7 1221-4282 W214 Southern California 7
HMC08 Seattle 7
HMC24 Seattle 4
W216-8 Southern California 5
105 Southern California 8
* GDCs = geographically dispersed clinical strains, GDCs were defined by the same LSP-MVR type being found for at least one580
clinical isolate at each of two or more geographical locations581
LSP-MVR = large-sequence polymorphism MIRU/VNTR analysis; PFGE = pulsed-field gel electrophoresis; LSP-MVR and582
PFGE types are given for all members of LSP-MVR-defined GDCs for which archived cultures from more than one location were583
available for PFGE analysis; identity by PFGE of isolates from distant geographic locations could only be tested for GDC1 and584
GDC7.585
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586
Figure legends587
Figure 1. Geographic distribution of large-sequence polymorphism MIRU/VNTR588
genotypes of clinicalMycobacterium avium. Area of pie charts is proportional to number of589
cases from each location included in analysis. Area of yellow circles corresponds to cachement590
areas of clinical lab(s) providing isolates or DNA for analysis. GDCs = geographically dispersed591
clinical strains; GDCs were defined by the same LSP-MVR type being found for at least one592
clinical isolate at each of two or more geographical locations; LSP-MVR = large-sequence593
polymorphism-MIRU/VNTR; digits of type represent loci HSDR, DA2/LSP2, DA7/LSP7,594
DEL11/LSPP5, X3, 25, 32, 47 (21,39); 1 is used to indicate the absence of the large-sequence595
polymorphism, which corresponds to product lengths of 343bp (for HSDR), 834bp (for596
DA2/LSP2), 329bp (for DA7/LSP7) and 728bp (for DEL11/LSPP5). 2 is used to indicate the597
presence of the large-sequence polymorphism, which corresponds to product lengths of 480bp598
(for HSDR), 954bp (for DA2/LSP2), 181bp (for DA7/LSP7) and 794bp (for DEL11/LSPP5)599
(21); digits for MIRU/VNTR type represent the number of repeats inferred from the product600
length at that locus based on product sizes and repeat numbers from Thibault et al (39) and601
personal correspondence with V. Thibault: 196bp when 2 repeats of 53bp are present (X3),602
350bp when 3 repeats of 58bp are present (25), 298bp when 8 repeats of 18bp are present (32)603
and 217bp when 3 repeats of 35bp are present (47); GDC 1 = 2112-3383, GDC 2 = 1111-5282,604
GDC 3 = 1121-3282, GDC 4 = 1211-2483, GDC 5 = 1211-4282, GDC 6 = 1221-3282, GDC 7 =605
1221-4282, GDC 8 = 2211-2283, GDC 9 = 2212-3383, GDC 10 = 1121-2282, GDC 11 = 1121-606
4282, GDC 12 = 2112-5383; local strains were defined by finding the same LSP-MVR type for607
two or more clinical isolates at a single geographic location, but not being found among clinical608
isolates from other geographic locations; unique types were found for a single isolate in the609
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entire set of clinical genotypes. Environmental isolates are not included in these numbers, and
were not considered in GDC designations. Genotypes for local clusters and unique types are
shown in Supplementary Table S5. The map is adapted from a Wikimedia Commons map
(http://commons.wikimedia.org/wiki/File:A_large_blank_world_map_with_oceans_marked_in_
blue-edited.png) published under a Creative Commons agreement.
Figure 2. Pulse-field gel electrophoresis of MA clinical isolates. Isolates were selected for this
analysis as described in the text. Panel A: Analysis of 11 isolates, including four from GDC1 and
three from GDC7. Panel B: Analysis of 14 isolates, including one from GDC1 and two from
GDC7. Numbers at the top of each lane indicate the isolate identity. Numbers at the bottom of
each lane indicate different PFGE patterns. (Isolates with same horizontal number have
indistinguishable patterns.) DNA markers in the far right lane (from bottom to top) are 48.5bp,
97.0bp, 145.5bp and 194.0bp.
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A B